Experimental or RCT research designs: a crisis of nomenclature in medical education
Bibliographic record
Abstract
Medical education research draws on a history of quantification espoused by the physical sciences and more recently framed by theorists and researchers from the education and psychological disciplines of the late 19th to early 20th centuries. In the 1920s, the tradition of experimental research design in education achieved a heightened period of interest with the work of psychologists like Edward Thorndike (i.e., his research on learning processes led to the scientific foundation for modern educational psychology). The evolution of quantitative research in medical education stems from researchers’ interest in using a systematic empirical methodology to investigate and develop models, theories and hypotheses related to educational phenomena.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.592 | 0.657 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.059 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".